An Eye for an Eye? An Integrated Model of Attitude Change Toward Protest Violence

Yuner ZHU, Edmund W. CHENG*, Fei SHEN, Richard M. WALKER

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

15 Citations (Scopus)

Abstract

How political violence emerges, why people support it, and how authorities can address it without escalating further radicalization remain an ongoing debate. In this study, we develop a quantitative model to predict violence endorsement as a function of repression severity, group identification, and individual emotions. We situate our investigation in the context of the Anti-Extradition Law Amendment Bill Movement in Hong Kong, during which the public acceptance of violence increased substantially, contrasting the city’s long history of peaceful protests. Results show that violence endorsement is associated with repression severity in a U-shaped fashion. While limited repression deters violence endorsement, excessive repression crossing a proportionality threshold escalates it. Group identification is a salient moderator that amplifies the backfire effects of repression. People who are more attached to protesting groups are more vigilant about repression and more supportive of protest violence. Furthermore, we also find that individual emotions exert more significant influences than repression and group identification. Anger, disgust, and fear can result in radicalized opinions. These findings unpack the complex and multifaceted communicative processes that shape the perceptions of protest violence. In contrast to the rational, organizational, and structural models of social movements, we argue that this analytical framework can offer more insights into protest dynamics amid the increasingly personalized political participation.
Original languageEnglish
Pages (from-to)539-563
Number of pages25
JournalPolitical Communication
Volume39
Issue number4
Early online date12 Apr 2022
DOIs
Publication statusPublished - 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© Copyright © 2022 The Author(s). Published with license by Taylor & Francis Group, LLC.

Funding

This work was supported by the Hong Kong Institute for Data Science (grant no. 9360163) and the Hong Kong Research Grants Council (grant no. 11605820).

Keywords

  • anti-extradition law amendment bill movement
  • Attitudinal radicalization
  • computational methods
  • emotion
  • Hong Kong
  • protest violence
  • repression

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